Title
Malasakit 2.0: A Participatory Online Platform with Feature Phone Integration and Voice Recognition for Crowdsourcing Disaster Risk Reduction Strategies in the Philippines
Abstract
We present Malasakit 2.0 (meaning “sincere care” in Filipino), an inclusive, multilingual participatory online platform with feature phone integration for collecting and analyzing quantitative and qualitative textual and audio data on disaster risk reduction (DRR) strategies. Malasakit 2.0 introduces interactive voice response (IVR) to support collection of audio data via feature phone. Malasakit utilizes peer-to-peer collaborative evaluation to identify and prioritize local DRR strategies. We present results from four field tests where 261 participants provided 1,582 evaluations of current DRR strategies, and over 950 peer-to-peer evaluations on 280 textual and audio suggestions for how local government (i.e., barangays) could better support vulnerable groups (e.g., elderly, women, children, and people with disabilities) during typhoons and floods. Results suggest that individuals who engage in disaster drills are also likely to participate in their barangay's clean-up drives to reduce flooding risk by clearing drainage pathways and that those who participate in disaster drills are also likely to have enough emergency supplies for a disaster. High-rated suggestions for DRR strategies for vulnerable groups emphasize the need for communities to establish response teams that prioritize reaching out to vulnerable groups for coordination during a disaster. Malasakit can be accessed at tiny.cc/Malasakit2.
Year
DOI
Venue
2018
10.1109/GHTC.2018.8601882
2018 IEEE Global Humanitarian Technology Conference (GHTC)
Keywords
Field
DocType
collaborative filtering,development assessment,participatory assessment,disaster risk reduction,canonical correlation analysis
Data collection,Internet privacy,Crowdsourcing,Computer science,Local government,Interactive voice response,Risk management,Citizen journalism,Disaster risk reduction,Feature phone
Conference
ISSN
ISBN
Citations 
2377-6919
978-1-5386-5567-2
0
PageRank 
References 
Authors
0.34
1
13